code: def _document_single_builder_inner(
      name: str,
      nightly_doc_util: doc_utils.NightlyDocUtil,
      **kwargs: Any,
  ) -> Optional[BuilderDocumentation]:
      """Doc string for a single builder, with or without configs."""
      tqdm.tqdm.write(f"Document builder {name}...")
      doc_info = _load_builder(name)
      if doc_info is None:
          logging.warning(
              "No doc info was found for document builder %s. Skipping.",
              name,
          )
          return None
  
      out_str = dataset_markdown_builder.get_markdown_string(
          namespace=doc_info.namespace,
          builder=doc_info.builder,
          config_builders=doc_info.config_builders,
          nightly_doc_util=nightly_doc_util,
          **kwargs,
      )
      is_nightly = bool(
          nightly_doc_util and nightly_doc_util.is_builder_nightly(name)
      )
      return BuilderDocumentation(
          name=name,
          filestem=name.replace(":", "_"),
          content=out_str,
          sections=doc_info.sections,
          is_manual=bool(doc_info.builder.MANUAL_DOWNLOAD_INSTRUCTIONS),
          is_nightly=is_nightly,
      )
  
imports: from concurrent import futures
  import dataclasses
  import functools
  from typing import Any, Iterator, List, Optional, Set, Type
  from absl import logging
  import tensorflow_datasets
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.scripts.documentation import collection_markdown_builder
  from tensorflow_datasets.scripts.documentation import dataset_markdown_builder
  from tensorflow_datasets.scripts.documentation import doc_utils
  import tqdm
label_desc: Use image node_id 10 for calling a global function with example usage: _document_single_builder_inner(name, nightly_doc_util) and returns: BuilderDocumentation, None